opencv单目摄像机标定（二）

 // 引入实际标定板方格宽度的标定程序
   #include <string>
   #include <iostream>
   #include <cv.h>
   #include <highgui.h>  
 
using namespace std;
 
int main()
{
CvCapture* capture; //摄像头指针
capture=cvCreateCameraCapture();
if(capture==){
printf("无法捕获摄像头设备！\n\n");
return ;
}else{
printf("捕获摄像头设备成功！！\n\n");
}
IplImage* frame; //图像指针
cvNamedWindow("摄像机帧截取窗口",);
printf("按“C”键截取当前帧并保存为标定图片...\n按“Q”键退出截取帧过程...\n\n");
int number_image=; //文件名后的编号，从1开始，也是截取的图像帧数
char filename[]=""; //保存文件名的字符串数组
while(true)
{
frame=cvQueryFrame(capture);
if(!frame)
break;
cvShowImage("摄像机帧截取窗口",frame);
 
if(cvWaitKey()=='c'){
sprintf (filename,"%d.jpg",number_image);
cvSaveImage(filename,frame);
cout<<"成功获取当前帧，并以文件名"<<filename<<"保存...\n\n";
printf("按“C”键截取当前帧并保存为标定图片...\n按“Q”键退出截取帧过程...\n\n");
number_image++;
}else if(cvWaitKey()=='q'){
printf("截取图像帧过程完成...\n\n");
cout<<"共成功截取"<<--number_image<<"帧图像！！\n\n";
break;
}
}
cvReleaseImage(&frame);
cvReleaseCapture(&capture);
cvDestroyWindow("摄像机帧截取窗口");
 
IplImage * show; //RePlay图像指针
cvNamedWindow("RePlay",);
int number_image_copy=number_image; //复制图像帧数
CvSize board_size=cvSize(,); //标定板角点数
CvSize2D32f square_size=cvSize2D32f(18.2,18.2); //cvSize2D32f( double width, double height );假设我的每个标定方格长宽都是1.82厘米
float square_length=square_size.width; //方格长度
float square_height=square_size.height; //方格高度
int board_width=board_size.width; //每行角点数
int board_height=board_size.height; //每列角点数
int total_per_image=board_width*board_height; //每张图片角点总数
int count; //存储每帧图像中实际识别的角点数
int found; //识别标定板角点的标志位
int step; //存储步长，step=successes*total_per_image;
int successes=; //存储成功找到标定板上所有角点的图像帧数
int a=; //临时变量，表示在操作第a帧图像
 
CvPoint2D32f * image_points_buf = new CvPoint2D32f[total_per_image]; //存储角点图像坐标的数组
CvMat * image_points=cvCreateMat(number_image*total_per_image,,CV_32FC1); //存储角点的图像坐标的矩阵
CvMat * object_points=cvCreateMat(number_image*total_per_image,,CV_32FC1); //存储角点的三维坐标的矩阵
CvMat * point_counts=cvCreateMat(number_image,,CV_32SC1); //存储每帧图像的识别的角点数
CvMat * intrinsic_matrix=cvCreateMat(,,CV_32FC1); //内参数矩阵
CvMat * distortion_coeffs=cvCreateMat(,,CV_32FC1); //畸变系数
 
while(a<=number_image_copy){
sprintf (filename,"%d.jpg",a);
show=cvLoadImage(filename,-);
found=cvFindChessboardCorners(show,board_size,image_points_buf,&count,
CV_CALIB_CB_ADAPTIVE_THRESH|CV_CALIB_CB_FILTER_QUADS);
if(found==){ //如果没找到标定板角点时
cout<<"第"<<a<<"帧图片无法找到棋盘格所有角点!\n\n";
cvNamedWindow("RePlay",);
cvShowImage("RePlay",show);
cvWaitKey();
 
}else{ //找到标定板角点时
cout<<"第"<<a<<"帧图像成功获得"<<count<<"个角点...\n";
cvNamedWindow("RePlay",);
IplImage * gray_image= cvCreateImage(cvGetSize(show),,);
cvCvtColor(show,gray_image,CV_BGR2GRAY);
cout<<"获取源图像灰度图过程完成...\n";
cvFindCornerSubPix(gray_image,image_points_buf,count,cvSize(,),cvSize(-,-),
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,,0.1));
cout<<"灰度图亚像素化过程完成...\n";
cvDrawChessboardCorners(show,board_size,image_points_buf,count,found);
cout<<"在源图像上绘制角点过程完成...\n\n";
cvShowImage("RePlay",show);
cvWaitKey();
}
 
if(total_per_image==count){
step=successes*total_per_image; //计算存储相应坐标数据的步长
for(int i=step,j=;j<total_per_image;++i,++j){
CV_MAT_ELEM(*image_points,float,i,)=image_points_buf[j].x;
CV_MAT_ELEM(*image_points,float,i,)=image_points_buf[j].y;
CV_MAT_ELEM(*object_points,float,i,)=(float)((j/board_width)*square_length);
CV_MAT_ELEM(*object_points,float,i,)=(float)((j%board_width)*square_height);
CV_MAT_ELEM(*object_points,float,i,)=0.0f;
}
CV_MAT_ELEM(*point_counts,int,successes,)=total_per_image;
successes++;
}
a++;
}
 
cvReleaseImage(&show);
cvDestroyWindow("RePlay");
 
cout<<"*********************************************\n";
cout<<number_image<<"帧图片中，标定成功的图片为"<<successes<<"帧...\n";
cout<<number_image<<"帧图片中，标定失败的图片为"<<number_image-successes<<"帧...\n\n";
cout<<"*********************************************\n\n";
 
cout<<"按任意键开始计算摄像机内参数...\n\n";
 
CvCapture* capture1;
capture1=cvCreateCameraCapture();
IplImage * show_colie;
show_colie=cvQueryFrame(capture1);
 
CvMat * object_points2=cvCreateMat(successes*total_per_image,,CV_32FC1);
CvMat * image_points2=cvCreateMat(successes*total_per_image,,CV_32FC1);
CvMat * point_counts2=cvCreateMat(successes,,CV_32SC1);
 
for(int i=;i<successes*total_per_image;++i){
CV_MAT_ELEM(*image_points2,float,i,)=CV_MAT_ELEM(*image_points,float,i,);
CV_MAT_ELEM(*image_points2,float,i,)=CV_MAT_ELEM(*image_points,float,i,);
CV_MAT_ELEM(*object_points2,float,i,)=CV_MAT_ELEM(*object_points,float,i,);
CV_MAT_ELEM(*object_points2,float,i,)=CV_MAT_ELEM(*object_points,float,i,);
CV_MAT_ELEM(*object_points2,float,i,)=CV_MAT_ELEM(*object_points,float,i,);
}
 
for(int i=;i<successes;++i){
CV_MAT_ELEM(*point_counts2,int,i,)=CV_MAT_ELEM(*point_counts,int,i,);
}
 
cvReleaseMat(&object_points);
cvReleaseMat(&image_points);
cvReleaseMat(&point_counts);
 
    //初始化相机内参矩阵
CV_MAT_ELEM(*intrinsic_matrix,float,,)=1.0f;
CV_MAT_ELEM(*intrinsic_matrix,float,,)=1.0f;
 
 //标定相机的内参矩阵和畸变系数向量
cvCalibrateCamera2(object_points2,image_points2,point_counts2,cvGetSize(show_colie),
intrinsic_matrix,distortion_coeffs,NULL,NULL,);
 
cout<<"摄像机内参数矩阵为：\n";
cout<<CV_MAT_ELEM(*intrinsic_matrix,float,,)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)
<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)
<<"\n\n";
cout<<CV_MAT_ELEM(*intrinsic_matrix,float,,)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)
<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)
<<"\n\n";
cout<<CV_MAT_ELEM(*intrinsic_matrix,float,,)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)
<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,,)
<<"\n\n";
 
cout<<"畸变系数矩阵为：\n";
cout<<CV_MAT_ELEM(*distortion_coeffs,float,,)<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)
<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)
<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)
<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,,)
<<"\n\n";
 
cvSave("Intrinsics.xml",intrinsic_matrix);
cvSave("Distortion.xml",distortion_coeffs);
 
cout<<"摄像机矩阵、畸变系数向量已经分别存储在名为Intrinsics.xml、Distortion.xml文档中\n\n";
 
CvMat * intrinsic=(CvMat *)cvLoad("Intrinsics.xml");
CvMat * distortion=(CvMat *)cvLoad("Distortion.xml");
 
IplImage * mapx=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,);
IplImage * mapy=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,);
 
cvInitUndistortMap(intrinsic,distortion,mapx,mapy);
 
cvNamedWindow("原始图像",);
cvNamedWindow("非畸变图像",);
 
cout<<"按‘E’键退出显示...\n\n";
 
while(show_colie){
IplImage * clone=cvCloneImage(show_colie);
cvShowImage("原始图像",show_colie);
cvRemap(clone,show_colie,mapx,mapy);
cvReleaseImage(&clone);
cvShowImage("非畸变图像",show_colie);
 
if(cvWaitKey()=='e'){
break;
}
 
show_colie=cvQueryFrame(capture1);
}
 
return ;
 
}